4 papers
Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization
Weiguo Zhou, Feng Zhang, Wenjin Qin +1
Robust tensor completion recovers multidimensional data from partial observations corrupted by sparse gross errors. Existing convolutional low-rank models typically construct trans…
Multi-Dimensional Visual Data Recovery: Scale-Aware Tensor Modeling and Accelerated Randomized Computation
Wenjin Qin, Hailin Wang, Jiangjun Peng +2
The recently proposed fully-connected tensor network (FCTN) decomposition has demonstrated significant advantages in correlation characterization and transpositional invariance, an…
Accelerating Large-Scale Regularized High-Order Tensor Recovery
Wenjin Qin, Hailin Wang, Jingyao Hou +1
Currently, existing tensor recovery methods fail to recognize the impact of tensor scale variations on their structural characteristics. Furthermore, existing studies face prohibit…
Hyperspectral Anomaly Detection Fused Unified Nonconvex Tensor Ring Factors Regularization
Wenjin Qin, Hailin Wang, Hao Shu +5
In recent years, tensor decomposition-based approaches for hyperspectral anomaly detection (HAD) have gained significant attention in the field of remote sensing. However, existing…